To the best of the author's knowledge, this is the first paper which considers both offline and online non-clairvoyant task offloading in mobile edge computing, together with analytical results on performance guarantee with high probability.
peer offloading:将任务或数据在分布式系统的各同级节点之间转移 mobile edge computing (MEC) Markov decision process (MDP) Deep Reinforcement Learning (DRL) Intelligent Task Offloading Scheme (INTO) 协作移动边缘计算是一种新兴的范式,允许分布式的MEC节点之间进行协同任务卸载,平衡计算负载。实际问题中,工作负载和...
According to the above DNN partitioning and task offloading strategy, for MDs with constrained computing and energy resources, task offloading to servers for processing is a feasible solution [21,22,23]. Some existing work focuses on the delay optimization in task offloading. Specifically, Li et a...
Mobile edge computing has been a promising paradigm to reduce the computation delay of tasks and extend the battery life of Internet of Things devices. Most existing task offloading methods in mobile edge computing networks are based on stable task arrivals and homogeneous users. However, in practic...
Game-based Pricing and Task Offloading in Mobile Edge Computing Enabled Edge-Cloud Systems 1Game-based Pricing and Task Off l oading in MobileEdge Computing Enabled Edge-Cloud SystemsYi Su, Wenhao Fan, Member, IEEE, Yuan’an Liu, Member, IEEE, and Fan WuAbstract—As a momentous enabling of...
Task Offloading Decision: BS n 还必须决定在网络边缘本地处理的任务数量。 令 b t n ∈ [0, 1] 为连续决策变量,表示在 BS n 本地处理的服务任务的比例。 解决问题的关键是什么? Lyapunov 优化,其实就是在线优化。 数据包的入队速度是a (t),出队速度是b(t),目标是是怎么样调整a(t),使得队列稳定,...
Caching and offloading in Mobile Edge Computing (MEC) are hot topics recently. Existing caching strategies at the edge ignore the programming ability of edge network and design strategies independently thus network resource is under utilization and the quality of experience (QOE) for end users is fa...
This method successfully copes with the complexity and dynamic challenges of task offloading in the mobile edge computing (MEC) environment, and shows strong application potential. Secondly, in terms of performance improvement, TL-DQN has cleverly introduced a transmission learning mechanism, which not ...
Energy-efficient task offloading, load balancing, and resource allocation in mobile edge computing enabled IoT networksEnergy-efficient task offloading, load balancing, and resource allocation in mobile edge computing enabled IoT networksresource allocationconvex...
注意,(12b)、(12c)、(12d)中的卸载决策约束X和(12e)、(12f)、(12g)中的RA策略P、F彼此是解耦的;因此,解决(13)中的问题相当于解决以下Task Offloading (to)问题: 其中J * (X)是RA问题对应的最优值函数,表示为: 注意,从问题(12)到问题(14)和问题(15)的分解并没有改变解的最优性[38]。在下一节中...